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Exchange Rate Fluctuations and Firm Leverage

IMF Economic Review volume 69, pages 90–121 (2021)Cite this article

Abstract

We quantify the effect of exchange rate fluctuations on firm leverage. When home currency appreciates, firms who hold foreign currency debt and local currency assets observe higher net worth as appreciation lowers the value of their foreign currency debt. These firms can borrow more as a result and increase their leverage. When home currency depreciates, the reverse happens as firms have to de-lever with a negative shock to their balance sheets. Using firm-level data for leverage from 10 emerging market economies during the period from 2002 to 2015, we show that firms operating in countries whose non-financial sectors hold more of the debt in foreign currency, increase (decrease) their leverage relatively more after home currency appreciations (depreciations). Combining the leverage data with firm-level FX debt data for 4 emerging market countries, we further show that our results hold at the most granular level. Our quantitative results are asymmetric: the effects of depreciations, that are generally associated with sudden stops, are quantitatively larger than those of appreciations, which take place at a slower pace over time during capital inflow episodes. As our exercise compares depreciations and appreciations of similar size, these results are suggestive of financial frictions being more binding during depreciations than a possible relaxation of such frictions during appreciations.

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Notes

  1. The evidence on such expenditure switching is, however, weak. Under dominant currency pricing, expenditure switching is muted as it works mostly via imports and not exports as shown by Gopinath (2016) and Gopinath et al. (2019).

  2. See Calvo and Reinhart (2002) who document a pervasive “fear of floating,” where the “fear” can be linked to liability dollarization. Another argument for preventing exchange rate volatility is the high degree of pass-through into domestic inflation in emerging market economies as argued by Burnstein and Gopinath (2014).

  3. Aguiar (2005), for example, considers the large depreciation episode during the 1995 Mexico debt crisis and finds that firms with heavy exposure to short-term FX debt before the devaluation experienced relatively low levels of post-devaluation investment. Kalemli-Ozcan et al. (2016), using also firm-level data from six Latin American countries, show that non-exporters with a balance sheet currency mismatch decrease investment as argued by Aguiar (2005), but that foreign-owned exporters with access to liquidity from their parents increase investment after currency crises in these countries. See also Serena and Sousa (2017) who show similar results for 36 emerging market economies. Bleakley and Cowan (2008) argue that exporters will not have a balance sheet currency mismatch due to their natural hedge of revenue in foreign currency. This might change if exporters are also importers since another channel for the contractionary effects of depreciations is imported intermediate inputs, where such inputs will be more expensive after a depreciation as shown in Mendoza and Yue (2012) and Gopinath and Neiman (2013).

  4. Bruno and Shin (2015b), using bank-level data, provide evidence that a depreciation of the US dollar against many countries’ currencies is associated with an increase in the leverage of global banks and an acceleration of cross-border banking flows into countries whose home currencies appreciate against the US dollar. Avdjiev et al. (2018a, 2018b) show similar evidence that cross-border banking flows are higher when there are depreciations in major funding currencies. On the pricing side, Hofmann et al. (2017, 2019) show that an appreciation of local currency vis-à-vis the US dollar in EMEs leads to a compression in government bond yields of those EMEs, which signals easier borrowing conditions for governments. See also Avdjiev et al.  (2019) and Avdjiev et al. (2018b) with similar results on prices. The literature still lacks evidence at the firm level on the direct effects of local currency appreciations on firms’ borrowing, a gap that our paper tries to bridge.

  5. See Adrian and Shin (2013) on the different cyclical properties of book leverage and market leverage. Although we do not have a mechanical valuation effect on firm leverage due to higher valued foreign currency assets when foreign currency appreciates and vice versa on debt, we have an accounting problem due to conversion of FX values to local currency. Under the accounting practice IAS 21 in IFRS standards that our sample economies use, the book values of foreign currency debt/assets are translated to local currency using the period-end exchange rates in firm balance sheets. Thus, with a 10 percent depreciation a 100 dollar loan that was booked as 100 pesos in local currency before the peso deprecation will now be booked as 110 pesos in local currency, although there is no new 10-peso local currency debt. This has to be adjusted to the original value of 100 dollars. We adjust for this “accounting effect” and show that it does not affect our results.

  6. The only exceptions are China and Hong Kong SAR. We ran robustness exercises without including these two economies and obtained similar results. Notice that the coverage of aggregate output and aggregate corporate sector debt in Worldscope data and in Capital IQ data will be much lower, around 10 percent, for all our sample economies due to the focus of these datasets on listed firms.

  7. We use continuous changes in the exchange rate as a robustness check.

  8. We find a marginally positive significant effect only in countries with high levels of FX debt at the beginning of the sample. Note that our results differ from those of Tong and Wei (2019) who find a very strong positive effect of FXI on firm leverage. We believe this is due to the small and select sample Tong and Wei (2019) use as they only focus on listed firms, whereas we have a much larger sample including private firms. Listed firms may increase their leverage as a result of FXI, but this does not mean country-level corporate sector leverage will be higher. The listed firms will not be representative of the corporate sector leverage in EMEs as they represent a small share of the corporate sector given less developed stock markets in these economies.

  9. We exclude from the sample the firms that are identified as “branches of foreign companies” and those with their headquarters or ultimate parents located outside the financial reporting country in terms of the ISO country code.

  10. In the literature, the market-to-book value or Tobin’s Q is typically used to control a firm’s growth opportunity. Since this is not available for non-listed firms in our sample, we use sales growth as a proxy for growth opportunity.

  11. The results are robust to clustering standard errors at the country level.

  12. The results are robust to clustering standard errors at the country level.

  13. This result is in line with Bleakley and Cowan (2008) who find no effect of balance sheet mismatch on investment of exporters.

  14. We thank Kim et al. (2015) for sharing their firm-level data for Korea and Kalemli-Ozcan et al. (2016) for sharing their firm-level data for Argentina, Brazil and Mexico.

  15. Our firm level data for Korea are for later years.

  16. To compare with country-level FX debt shares, we calculate Korean firms’ average debt-to-liability ratio based on our ORBIS sample, which is around 0.6, and then estimate the FX debt-to-total debt ratio by dividing the foreign debt-to-liability ratio by 0.6. This is because Korean data only report total liability and not total debt, which is what we use due to the existence of non-financial obligations in the total liability item as argued in the data section.

  17. Kalemli-Ozcan (2019) shows that using monetary policy to limit the exchange rate fluctuations during crises in countries with high levels of FX debt can be counter-productive.

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Authors and Affiliations

  1. University of Maryland, NBER and CEPR, College Park, USA

    Sebnem Kalemli-Ozcan

  2. Bank for International Settlements, Hong Kong, SAR, China

    Xiaoxi Liu & Ilhyock Shim

Authors
  1. Sebnem Kalemli-Ozcan
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  2. Xiaoxi Liu
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  3. Ilhyock Shim
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Correspondence to Sebnem Kalemli-Ozcan.

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We thank participants in numerous conferences and seminars. We are grateful to Jimmy Shek and Jose Maria Vidal Pastor for research assistance. This article reflects the views of the authors and does not necessarily reflect those of the Bank for International Settlements.

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Appendix

Appendix

We go through the following five steps to calculate FX debt at the firm level:

  1. 1.

    Total FX debt in an economy The BIS Global Liquidity Indicator (GLI) database provides total FX debt data at the country level, which consist of data on debt securities denominated in the US dollar, euro and Japanese yen and issued by the non-financial sector entities in a country and data on bank loans denominated in the US dollar, euro and Japanese yen and extended to the non-bank sector entities in the country. Bank loans include both cross-border bank loans and locally extended bank loans. The non-financial sector includes non-financial firms, households and the government, while the non-bank sector includes non-bank financial firms in addition to the non-financial sector. The debt securities data are from the BIS International Debt Securities Statistics, while the bank loan data from the BIS Locational Banking Statistics. The BIS International Debt Securities Statistics also provide data on the value of FX-denominated debt securities issued by the government. In order to focus on FX-denominated debt securities issued by non-financial firms, we subtract the value of FX-denominated debt securities issued by the government from total FX debt. When we use the country-level total FX debt, the values denominated in the euro and Japanese yen are converted into those in the US dollar using the quarter-end exchange rate.

  2. 2.

    Total credit to the non-financial sector The BIS total credit database provides data on total credit to the non-financial sector. Total credit includes all forms of credit (including both loans and debt securities) extended by banks and non-banks in all currencies. The database also provide data on total credit broken down into the following three sectors: non-financial firms, households and the government.

  3. 3.

    Based on (1) and (2), we compute the FX debt share of each country as the ratio of FX debt to total credit to the non-financial sector. Note that both FX debt and total credit include both loans and debt securities.

  4. 4.

    Firm-level total debt From the ORBIS database, we obtain the value of total debt outstanding reported in the balance sheets of each firm’s annual reports.

  5. 5.

    Finally, we multiply the FX debt share for an economy by firm-level total debt for all firms located in the economy, to estimate the amount of firm-level FX debt outstanding.

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Kalemli-Ozcan, S., Liu, X. & Shim, I. Exchange Rate Fluctuations and Firm Leverage. IMF Econ Rev 69, 90–121 (2021). https://doi.org/10.1057/s41308-020-00130-4

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